Latest AI and machine learning research in oncology/hematology for healthcare professionals.
The advent of high-throughput sequencing technologies, such as DNA microarray and DNA sequencing, ha...
The most prevalent malignancy among women is breast cancer; hence, treatment approaches are needed i...
Intratumor heterogeneity (ITH) is involved in tumor evolution and drug resistance. Drug sensitivity ...
BACKGROUND: Natural language processing systems for data extraction from unstructured clinical text ...
PURPOSE: To explore the development and validation of automated machine learning (AutoML) models for...
BACKGROUND: Although immune checkpoint inhibitor (ICI) represents a significant breakthrough in canc...
With the rising demand for liver transplantation (LT), research on acute rejection (AR) has become i...
Equitable cancer care in low- and middle-income countries is crucial as mortality rates continue to ...
The aim was to evaluate a deep learning-based auto-segmentation method for liver delineation in Y-90...
INTRODUCTION: The use of artificial intelligence in hematology laboratories has improved the diagnos...
Longitudinal liver tumor segmentation plays a fundamental role in studying and monitoring the progre...
BACKGROUND CONTEXT: A machine learning (ML) model was recently developed to predict massive intraope...
Liquid biopsy (LB) has emerged as a transformative tool in oncology, providing a minimally invasive ...
BACKGROUND AND OBJECTIVE: In the medical field of digital pathology, many tasks rely on visual asses...
PURPOSE: This study aims to develop an artificial intelligence model to predict severe radiation-ind...
Despite improvements in machine learning algorithms applied to digital pathology, only moderate accu...
Liquid biopsies are an emerging, noninvasive tool for cancer diagnostics, utilizing biological fluid...
Immunotherapy and chemoimmunotherapy are standard treatments for non-oncogene-addicted advanced non-...
BACKGROUND: Catheter-related thrombosis (CRT) is a serious complication in cancer patients undergoin...
Single-cell RNA sequencing (scRNA-seq) is a powerful tool for characterizing tumor heterogeneity, ye...
Spatial omics technologies enable analysis of gene expression and interaction dynamics in relation t...